The Impacts of Profitability, Liquidity, Leverage, Firm Size, and Free Cash Flow

International Journal of Business, Economics and Law, Vol. 22, Issue 1 (AUGUST) ISSN 2289-1552 2020

FINANCIAL DISTRESS: THE IMPACTS OF PROFITABILITY, LIQUIDITY, LEVERAGE, FIRM SIZE, AND FREE CASH FLOW

Angela Dirman

ABSTRACT

The research objective to be achieved is to provide understanding and knowledge to the public, especially investors and creditors about the effect of profitability, liquidity, leverage, company size, and free cash flow on financial distress and can be used as a reference for future researchers and stakeholders (investors, creditors, and government) in making relevant and reliable decisions. The method used is quantitative research with secondary data taken from the issuer's financial statements on IDX with data collection techniques using the purposive sampling method. Analysis of the data used is multiple linear regression. The population in this research is manufacturing companies of basic and chemical industry sectors which are listed on the Indonesia Stock Exchange which is conducted for 3 years of observation, namely 2016-2018. The sample is determined by the purposive sampling method so that as many as 90 samples are obtained. The analysis technique used is the statistical test t, and the classic assumption test which includes normality test, multicollinearity test, heterokedasticity test, and autocorrelation test. The results of this study indicate that the profitability variable has a positive effect on financial distress; variable liquidity, leverage, and free cash flow do not effect financial distress; and firm size variables have a negative effect on financial distress

Keywords: Profitability, Liquidity, Leverage, Company Size, Free Cash Flow, Financial Distress

INTRODUCTION

The global economic crisis is an event in which all sectors of the world market economy experience collapse (degression) and affect other sectors throughout the world. The global economic crisis occurs due to unavoidable market economic problems around the world due to bankruptcy and turbulent economic situations. The most visible sector due to the effects of the global economic crisis is the economic sector from the smallest to the largest. Including stock exchanges in the Middle East, Russia, Europe, South America and North America. No exception in the US itself, investors on the Wall Street Exchange suffered huge losses. In Indonesia, the real sector has been affected by the global crisis. The sectors most affected by the global crisis are those that rely on external (tradable) demand, such as the manufacturing, agriculture and mining industries (kompas.com). In addition to the global financial crisis, the start of free trade between ASEAN countries also affected the company's performance. The more freely foreign companies enter Indonesia, the competition between companies is increasing. Companies that cannot survive facing the situation indicate that the company has experienced failure which is indicated by financial distress. Companies that experience financial distress will experience difficulties in generating profits in a reporting period, besides that the company also experiences difficulties in fulfilling its short-term obligations to third parties such as investors, creditors and employees (Rahmawati, 2014).

As in manufacturing companies that are not free from financial problems. One of the companies experiencing financial distress is PT Citra Maharlika Nusantara Corpora Tbk. (Cipaganti). The company previously named PT Cipaganti Citra Graha Tbk was declared bankrupt on April 27, 2017 because the peace proposal was rejected by the majority of creditors. This bankruptcy case also stems from the PKPU Cipaganti status since October 31, 2016. The company's total debt amounts to IDR245 billion. Another case that befell a company listed on the IDX is PT. Berau Coal Energy, which was sued for bankruptcy by creditors because it failed to pay off maturing debts. PT. Berau Coal Energy Tbk has defaulted its US $ 450 bond debt maturing on July 8, 2015. The 12.5 percent coupon bond was issued by Berau Resources Pte Ltd in Singapore and guaranteed by PT. Berau Coal Energy Tbk. The delay in repaying the debt is then interpreted as the inability of the company to settle its debt burden so that it is reported to have gone bankrupt or bankruptcy.

According to Platt & Platt (2002) financial distress has been defined as a decrease or even a condition of decline. Financial distress becomes an interesting topic in the financial sector and financial health companies as an important indicator for users who are interested in knowing more about company performance (Pernamasari, Purwaningsih, Tanjung, & Rahayu, 2019). Information regarding finances is used by people who are at the same time as people who are at an early age. So that the damage and even the parties to the worst conditions are still very poor. When a company experiences financial difficulties, it will be a consideration for investors and creditors who will invest their capital. Thus, companies should be able to show good company performance to be able to attract investors (Widhiari & Aryani Merkusiwati, 2015).

The performance of an entity can be seen from the analysis of financial statements. The results of the analysis of an entity's financial statements can be used as material for decision making and decision making for company owners, managers and investors. Financial statement ratio analysis can azlso be used as a medium to predict financial difficulties faced by companies (Widhiari & Aryani Merkusiwati, 2015). Prediction errors in the future will be fatal in the survival of the company, prediction errors result in loss of income or investment that has been invested into the company. The importance of a bankruptcy prediction analysis is very much needed by several related parties, such as investors, banks, the government, and primarily the company itself. The correct prediction will also make the company know in advance the company's financial condition (Rohmadini, Saifi, & Darmawan, 2018). According to Li & Du (2011) research on financial distress generally uses financial indicators to predict the condition of a company in the future. Financial indicators in this study are profitability ratios, liquidity ratios, and leverage. In addition to using indicators of corporate financial performance, in this study there are also other factors namely firm size and free cash flows.

International Journal of Business, Economics and Law, Vol. 22, Issue 1 (AUGUST) ISSN 2289-1552 2020

Profitability is the company's ability to generate profits. Where profit is one indicator of how well the company's performance. Profitability includes all revenues and costs incurred by the company as the use of assets and liabilities in a period. The main purpose of the company is to have high profits. High profits will increase the welfare of its shareholders and will increase the interest of investors to invest their funds in the company. High profits will also illustrate the level of success of the company in carrying out its operational activities (Rohmadini et al., 2018). If the level of profitability of the company is getting higher, it is unlikely that the company will experience financial distress. Ananto, Mustika, & Handayani (2017) and Curry & Banjarnahor (2018) in their research found that profitability had a negative effect on financial distress, but in Rohmadini et al., (2018) profitability measured by ROA had no effect on financial distress.

In addition to profitability, financial distress can also be predicted through a liquidity ratio. Liquidity ratio is the ratio used to measure how liquid a company is (Kasmir, 2012). Short-term creditors are very concerned with this current ratio because the conversion of inventories and accounts receivable to cash is the main source, from which companies can wash cash to pay short- term creditors. From the point of view of short-term creditors, the higher the current ratio of companies the greater the protection (Gamayuni in Triwahyuningtias & Muharam (2012). Curry & Banjarnahor (2018) found that liquidity had a negative effect on financial distress, while the results of Rohmadini et al., (2018) and Cinantya & Merkusiwati (2015) in their research found that there was no effect of liquidity on the possibility of financial distress.

Besides financial distress can also be predicted through financial leverage. Leverage ratio is a ratio used to measure the extent to which a company's assets are financed from debt. Leverage indicates an influence on investment rates and investment opportunities in companies where the level of debt of a company will indirectly affect the interests and trust of investors in investing (Rohmadini et al., 2018). High and low corporate debt will affect the size of the risk of financial distress that will be borne by the company. Rohmadini et al., (2018), and Curry & Banjarnahor (2018) in their research found that leverage has a negative effect on financial distress, while research results from Bernardin & Tifani (2019) in their research found that there was no effect of leverage on financial distress.

In addition to the above ratio, financial distress can also be predicted through firm size. The firm size illustrates how the total assets owned by the company. The greater the company's total assets, the company's financial condition will be more stable and stronger in dealing with the possibility of bankruptcy in the future. Bernardin & Tifani (2019) in their research found that there was a significant influence with a negative direction between cash flows in predicting financial distress.

In addition, financial distress can also be predicted through stress cash flow. According to Sayari & Mugan (2017) cash flow has relevant information in identifying the financial health or setbacks of a company. If the company has a good amount of cash flow, then creditors will get the confidence that the company is able to perform its obligations and the company avoids financial distress (Tutliha & Rahayu, 2019). This further illustrates the importance of the role of cash flow in determining the smooth running of company activities. Bernardin & Tifani (2019) in their research stated that good free cash flow can minimize the potential for financial difficulties in the future.

LITERATURE REVIEW

Signalling Theory Signal theory is an action taken by company management to provide instructions to investors about how management assesses the company's prospects. The management will try to improve company performance where by increasing performance the company's profits will also increase. Signal theory provides information to external parties about the company's future conditions (Scott, 2014: 305). Information provided by the company can be in the form of good news such as good company conditions, earnings announcements, dividend distribution and bad news information can be in the form of corporate losses so that they cannot divide dividends, or too much corporate debt thereby increasing the risk of bankruptcy.

Financial Distress Financial Distress is a condition in which the company is experiencing financial difficulties. According to Platt & Platt (2002) financial distress is the stage of decline in financial conditions that occurs before bankruptcy occurs. Information regarding finances is used by people who are at the same time as people. So that damage and even those who have an important role can make an effort to take part in a very destructive life. When the company experiences financial difficulties, it will be a consideration for investors and creditors who will invest. So, the company should be able to show good company performance in order to attract investors (Widhiari & Aryani Merkusiwati, 2015).

There are three approaches to assessing a company's financial vulnerability. Saji (2018) in Pernamasari et al., (2019) said that the three approaches are statistical approaches based on the inequality between current assets and short-term liabilities, both the functional approach and the third approach to the Z-Score approach. The Altman Z Score Bankruptcy Risk Prediction Model is a multivariable equation used by Altman in order to predict the bankruptcy rate of a company. Altman uses a statistical model called discriminant analysis, to be precise is multiple discriminant analysis (MDA).

MDA came into use in biological research in the 1930's. In the MDA the sample is divided into two groups, in this case the companies that are bankrupt and the companies that are not bankrupt. This Z-Score analysis was developed in 1968 by Edward I. Altman. In his research (Altman, 1968) took a sample of 66 public manufacturing companies located in America consisting of 33 companies that went bankrupt and 33 companies selected randomly that never went bankrupt. Altman calculated 22 ratios to test. From this number, only the 5 ratios that have the strongest correlation with bankruptcy are selected.

International Journal of Business, Economics and Law, Vol. 22, Issue 1 (AUGUST) ISSN 2289-1552 2020

Altman formed 3 Z Score formulas where the three formulas are intended for 3 different company categories, namely for publicly listed companies, closed companies, and for non-manufacturing public companies. This study uses the Altman Zscore model for a public manufacture company, such as Pernamasari et al., (2019). Where shares or shares of a company are traded openly or listed on a stock exchange. The formula used is as follows:

Z = 1,2 (X1) + 1,4 (X2) + 3,3 (X3) + 0,6 (X4) + 1,0 (X5)

Information: Z = Bankruptcy Indeks X1 = Working Capital/Total Assets X2 = Retained Earnings/Total Assets X3 = Earning Before Interest and Taxes/Total Assets X4 = Market Value of Equity/Book Value of Debt X5 = Sales/Total Assets Score Condition> 2.99 Not Bankrupt, 1.81 - 2.99 Gray Area, <1.81 Bankrupt

Profitability Profitability ratio is a ratio to assess the company's ability to seek profit or profit in a certain period (Kasmir, 2014: 15). Profit is one indicator of how well the company is performing. Profitability includes all revenues and expenses incurred by the company as the use of assets and liabilities in a period. The main purpose of the company is to have high profits. High profits will increase the welfare of its shareholders and will increase the interest of investors to invest their funds in the company. High profits will also illustrate the company's success rate in carrying out its company's operational activities (Rohmadini et al., 2018).

Liquidity The liquidity ratio is a ratio used to measure how liquid a company is (Kasmir, 2012). A company can be said to be liquid if the company is able to settle its short-term obligations at maturity. When the liquidity ratio is high, the company has the ability to meet its short-term debt obligations. According to Syamsuddin (2011: 43-44), the current ratio can be determined by comparing current assets with current liabilities. There is no absolute measure of how much the current ratio is considered good or should be maintained by a company because usually this level of current ratio also depends on the type of business of each company.

Leverage Leverage ratio is the ratio used to measure the extent to which company assets are financed from debt. Leverage shows an influence on investment rates and investment opportunities in companies where the level of debt from a company will indirectly affect investor interest and confidence in investing (Rohmadini et al., 2018). High and low corporate debt will affect the size of the risk of financial distress that will be borne by the company. Debt to Equity Ratio (DER) is the ratio used to assess debt to equity. This ratio is found by comparing all debt, including current debt, and total equity.

Firm Size Firm size describes how much total assets the company has. According to Sayari & Mugan (2017) cash flow has relevant information in identifying the financial health or decline of a company. This further illustrates the importance of the role of cash flow in determining the smooth running of company activities.

Free Cash Flow Free cash flow according to Ross et al in Nisa & Triyanto (2018) is company cash that can be distributed to creditors or shareholders which is not used for working capital or investment in fixed assets. Operating cash flow information is an indicator for creditors to find out the company's financial condition. Free cash flow can be used for discretionary uses such as acquisitions and growth- oriented capital expenditures, debt payments, and payments to shareholders in the form of dividends. This means that the greater the free cash flow available in the company, the healthier the company is because it has cash available for growth, debt payments, and dividends. According to Sayari & Mugan (2017) cash flow has relevant information in identifying the financial health or decline of a company. If the company has a good amount of cash flow, creditors will have confidence that the company is able to carry out its obligations and the company will avoid financial distress (Tutliha & Rahayu, 2019). This further illustrates the importance of the role of cash flow in determining the smooth running of company activities.

Effect of profitability on financial distress Profitability is the company's ability to generate profits. Where profit is one indicator of how well the company's performance. Profitability includes all revenues and costs incurred by the company as the use of assets and liabilities in a period. The main purpose of the company is to have high profits. High profits will increase the welfare of its shareholders and will increase the interest of investors to invest their funds in the company. High profits will also illustrate the level of success of the company in carrying out its operational activities (Rohmadini et al., 2018). If the level of profitability of the company is getting higher, it is unlikely that the company will experience financial distress (Gobenvy, 2014). Ananto et al., (2017) and Wahono, Mardani, & Suproho (2017) in their research found that profitability has a negative effect on financial distress. The following hypotheses are proposed: H1: Profitability has a negative effect in predicting Financial Distress.

International Journal of Business, Economics and Law, Vol. 22, Issue 1 (AUGUST) ISSN 2289-1552 2020

Effect of Liquidity on financial distress Liquidity ratio is the ratio used to measure how liquid a company is (Kasmir, 2012). A company can be said to be liquid if the company is able to settle its short-term obligations when due. When the value of the liquidity ratio is high, the company has the ability to meet its short-term debt obligations. If the company is in a liquid condition, the company will automatically be able to overcome financial distress. In Wahono et al. (2017) research, liquidity has a negative effect on predicting financial distress. The following hypotheses are proposed: H2: Liquidity has a negative effect in predicting Financial Distress.

Effect of Leverage on financial distress Leverage ratio is a ratio used to measure the extent to which a company's assets are financed by debt. Leverage arises from the activity of using company funds from third parties in the form of debt. The use of this funding source will result in the obligation arising for the company to return the loan along with interest on the loan. If this situation is not matched by a good company income, it is likely that the company will easily experience financial distress (Gobenvy, 2014). Rohmadini et al. (2018) in his research found the results that leverage affects financial distress. The following hypotheses are: H3: Leverage has a negative effect in predicting Financial Distress

Effect of Firm Size on Financial Distress The size of a company illustrates how big the total assets owned by the company. Companies that have a large total assets show a positive signal for creditors because the company will easily diversify and be able to pay off obligations in the future, so the company can avoid financial distress. In research Susilawati, Sofianty, & Sukarmanto (2017) said that company size has a negative effect on financial distress. The following hypotheses are proposed: H4: Firm size has a negative effect in predicting Financial Distress.

Effect of Free Cash Flow on financial distress Operating cash flow information is an indicator for creditors to find out the company's financial condition. If the company has a good amount of cash flow, then creditors will get the confidence that the company is able to carry out its obligations and the company avoids financial distress. The following hypotheses are proposed: H5: Free Cash Flow has a negative effect in predicting Financial Distress.

RESEARCH METHOD

Definition and Operationalization of Variables Dependent variable Altman forms 3 Z Score formulas in which the three formulas are for 3 different categories of companies, namely for publicly traded companies, closed companies, and for non-manufacturing public companies. This study uses the altman zscore model for public manufacturing companies as in the research Pernamasari et al., (2019). Where shares or shares of a company are traded openly or listed on a stock exchange. The formula used is as follows:

Z = 1,2 (X1) + 1,4 (X2) + 3,3 (X3) + 0,6 (X4) + 1,0 (X5)

Independent Variable

Profitability Profitability Ratios are ratios to assess a company's ability to look for profits or profits for a certain period. The ratio used in this study is Return On Assets (ROA) with calculations (Kasmir, 2019): ROA = Net Profit / Total Assets

Liquidity Liquidity ratio is the ratio used to measure how liquid a company is (Kasmir, 2012). The formula of the Current ratio (Syamsuddin, 2011: 43): Current Ratio = Current Asset Current Liabilities

Leverage The Solvency Ratio is a ratio used to measure the extent to which a company's assets are financed with debt. The ratio used in this study is Debt to equity ratio (DER) with calculations (Kasmir, 2019): DER = Total Debt Equity

International Journal of Business, Economics and Law, Vol. 22, Issue 1 (AUGUST) ISSN 2289-1552 2020

Firm Size Asset value is used to measure the firm size, the value of these assets is measured as a logarithm of total assets. Measurement of firm size variables are as follows: Firm Size = Ln Total Assets

Free Cash Flow Free cash flow is free company cash that can be distributed to creditors or shareholders that are not used for working capital or investment in fixed assets. The formula for calculating free cash flow is: Free Cash Flow = CFO – Net Capital Expenditure – Net Borrowing

Population and Research Samples The population of this study is companies listed on the Indonesia Stock Exchange. The samples used in this study are industrial and chemical manufacturing companies listed on the Indonesia Stock Exchange in 2016-2018. The sampling method used was purposive sampling, which is sampling based on the criteria of companies that consistently list on the IDX in the study year and use the rupiah in their financial statements.

Analysis Method In testing the hypothesis proposed in this study. The researcher uses the method of multiple linear regression analysis because of the relationship between two or more independent variables where previously the classical assumptions were made in the first stage.

Classical Assumption Test This analysis can also be referred to as a prerequisite test of the multiple linear regression model to be tested. A good regression model must produce the best unbiased linear estimator (Best Linear Unbias Estimator / BLUE). This condition will occur if it is fulfilled by several assumptions called classical assumptions including normality test, multicollinearity test, heteroscedasticity test, autocorrelation test. The regression model in this study is stated as follows:

Z-score = a + β1ROA + β2CR + β3DER + β4Size + β5FCF + e

RESULTS AND DISCUSSION

Results Classical Assumption Test Normality test

Kolmogorov-Smirnov One Sample Results

Tabel. 1 One-Sample Kolmogorov-Smirnov Test Unstandardized Residual N 90 Mean .0000000 Normal Parametersa,b Std. Deviation .57337362 Absolute .068 Most Extreme Differences Positive .051 Negative -.068 Kolmogorov-Smirnov Z .647 Asymp. Sig. (2-tailed) .797 a. Test distribution is Normal. b. Calculated from data.

The table above shows that the Kolmogorov-Smirnov value is 0.647 and the Asymp value. Sig. (2-tailed) of 0.797. Because the Asymp value. Sig is greater than the significance level of 0.05 (0.797> 0.05), it can be concluded that the residual data in this regression model is normally distributed.

Multicollinearity Test Tabel. 2 Coefficientsa Model Unstandardized Standardized t Sig. Collinearity Statistics Coefficients Coefficients B Std. Error Beta Tolerance VIF (Constant) 4.758 1.375 3.459 .001 ROA 14.366 1.258 .798 11.423 .000 .738 1.354 CR .034 .033 .075 1.020 .311 .662 1.512 1 DER -.444 .373 -.073 -1.190 .238 .962 1.040 SIZE -.128 .048 -.185 -2.695 .009 .766 1.306 FCF -.541 .428 -.079 -1.263 .210 .912 1.097

International Journal of Business, Economics and Law, Vol. 22, Issue 1 (AUGUST) ISSN 2289-1552 2020

a. Dependent Variable: ZSCORE

There is no multicolliniarity among the independent variables. Then there is no multicolliniarity between the independent variables.

Heteroskedaticity Test

Tabel. 3 Coefficientsa Model Unstandardized Standardized T Sig. Collinearity Statistics Coefficients Coefficients B Std. Error Beta Tolerance VIF (Constant) -.076 .796 -.095 .925 ROA -.400 .728 -.069 -.550 .584 .738 1.354 CR .010 .019 .066 .496 .621 .662 1.512 1 DER -.212 .216 -.108 -.981 .330 .962 1.040 SIZE .019 .028 .087 .709 .480 .766 1.306 FCF -.206 .248 -.094 -.831 .408 .912 1.097 a. Dependent Variable: Abs_RES

The profitability, liquidity, leverage, company size and FCF variables in the heteroscedasticity test show that there was no heteroscedasticity, it can be seen from the sig value of each variable more than 0.05.

Autocorrelation Test

Tabel. 4 Model Summaryb

Model R R Square Adjusted R Square Std. Error of the Durbin- Estimate Watson

1 ,835a ,697 ,679 ,5901917 2,091

a. Predictors: (Constant), FCF, SIZE, DER, CR, ROA b. Dependent Variable: ZSCORE

Then there is no autocorrelation between the independent variables.

Hypothesis testing Determination Coefficient Test

Tabel. 5 Model Summaryb Model R R Square Adjusted R Square Std. Error of the Durbin-Watson Estimate 1 ,835a ,697 ,679 ,5901917 2,091 a. Predictors: (Constant), FCF, SIZE, DER, CR, ROA b. Dependent Variable: ZSCORE

In the table above shows that the coefficient of determination that shows the value of the R-square of 0.697. This means that 69.7% variation in financial distress can be explained significantly by variations in ROA, CR, DER, Company Size, and Free Cash Flow While (100% - 69.7%) = 30.3% the amount of financial distress can be explained by other variables.

F Test

Tabel. 6 ANOVAa Model Sum of df Mean Square F Sig. Squares Regression 67.325 5 13.465 38.656 .000b 1 Residual 29.259 84 .348 Total 96.584 89 a. Dependent Variable: ZSCORE b. Predictors: (Constant), FCF, SIZE, DER, ROA, CR

Based on the data above, a significant value of 0,000 is obtained. Because the significance is less than 0.05 or 5% then Ho is rejected and Ha is accepted, so it can be concluded together profitability, liquidity, leverage, company size, and free cash flow affect financial distress.

International Journal of Business, Economics and Law, Vol. 22, Issue 1 (AUGUST) ISSN 2289-1552 2020

T Test

Tabel. 7 Coefficientsa Model Unstandardized Standardized t Sig. Coefficients Coefficients B Std. Error Beta (Constant) 4.758 1.375 3.459 .001 ROA 14.366 1.258 .798 11.423 .000 CR .034 .033 .075 1.020 .311 1 DER -.444 .373 -.073 -1.190 .238 SIZE -.128 .048 -.185 -2.695 .009 FCF -.541 .428 -.079 -1.263 .210 a. Dependent Variable: ZSCORE

From the above test results it can be concluded as follows:

1. This shows that ROA has a positive influence on Financial Distress. 2. Concluded that Liquidity has no effect on Financial Distress. 3. Concluded that Leverage has no effect on Financial Distress. 4. Concluded that Company Size has a negative effect on Financial Distress. 5. Concluded that Free Cash Flow has no effect on Financial Distress.

Multiple Regression Analysis Test Results

Tabel. 8 Coefficientsa Model Unstandardized Standardized t Sig. Coefficients Coefficients B Std. Error Beta (Constant) 4.758 1.375 3.459 .001 ROA 14.366 1.258 .798 11.423 .000 CR .034 .033 .075 1.020 .311 1 DER -.444 .373 -.073 -1.190 .238 SIZE -.128 .048 -.185 -2.695 .009 FCF -.541 .428 -.079 -1.263 .210 a. Dependent Variable: ZSCORE

Based on the table of the results of multiple linear regression tests, the regression equation is obtained as follows: Zscore = 4,758 + 14,366 ROA + 0,034 CR + (-0,444 DER) + (-0,128 SIZE) + (-0,541 FCF) + e

DISCUSSION

Effect of Profitability on Financial Distress The test results show that profitability has a positive effect on financial distress. Based on the results of the T test shows that the profitability variable which is calculated by the return of assets has a positive effect on financial distress. That is, the higher the ratio of return of assets, the financial distress as measured by the z-score is higher. High return on assets shows the company's ability to use existing assets to produce well. The more effective and efficient management of company assets can produce better profits and optimal use of funds. However, there are some companies that are able to generate high profits but are unable to control the adequacy of existing funds to cover the costs and to run their business, so that the company will experience financial distress. An increase in ROA does not indicate that the company is avoiding financial distress. It is said so because the company can see from the revenue and the amount of costs incurred. Increasing costs and decreasing revenues from year to year can result in a number of net losses that increase from year to year, so that the company can experience financial distress. The results of this study are in line with the results of previous research by Asfali (2019) which states that profitability has a positive effect on financial distress.

Effect of Liquidity on Financial Distress The results showed that the liquidity variable measured by the current ratio had no effect on financial distress. By comparing the total current assets owned by the company with total current liabilities. In current assets there are accounts and trade receivables accounts which, if later will be used to pay the company's current liabilities, require considerable time and vary between companies to convert accounts receivable and inventories in cash which will be used to finance company liabilities. So any amount of company liquidity will not affect the possibility of the company experiencing financial distress. The results of this study support previous research Srikalimah (2017) and Rohmadini et al. (2018) that liquidity has no effect on financial distress.

Effect of Leverage on Financial Distress The test results show leverage does not affect financial distress. In other words, the size of the DER value is not an appropriate predictor to measure the company's financial distress. Companies with high DERs are not necessarily categorized as companies

International Journal of Business, Economics and Law, Vol. 22, Issue 1 (AUGUST) ISSN 2289-1552 2020 that experience financial distress, nor do companies with lower DER values are not necessarily categorized as non-financial distress companies. This is due to the high total liabilities of the company but the total assets owned by the company are also high, so the company is able to pay liabilities with the assets owned. These results are consistent with research conducted by Sporta, Ngugi, Ngumi, & Nanjala (2017), Bernardin & Tifani (2019), Srikalimah (2017) and Tutliha & Rahayu (2019) which resulted in Debt Equity Ratio (DER) research having no effect on financial distress.

Effect of Firm Size on Financial Distress The test results show that company size has a negative effect on financial distress. The size of the company measured by using total assets, has a negative influence on financial distress, because the greater the total assets owned by the company will have an impact on the increasing ability to pay off corporate obligations in the future, so that the company can avoid financial problems. The results of this study are supported by research Susilawati et al. (2017) who found that company size has a negative effect on financial distress.

The Effect of Free Cash Flow on Financial Distress Test results show that free cash flow has no effect on financial distress. This means that there is no significant effect between free cash flow and financial distress. The size of the cash flow does not affect the company's financial distress. No influence of cash flow on financial distress due to the amount of fluctuating cash flow in the sample companies that experienced financial distress and non-financial distress companies.

CONCLUSION

Based on the results of the analysis and discussion explained in the previous chapter, the conclusions of this study are as follows: 1. Profitability has a positive effect on financial distress. 2. Liquidity does not influence Financial Distress. 3. Leverage has no effect on Financial Distress. 4. Company size has a negative effect on Financial Distress. 5. Free Cash Flow has no effect on Financial Distress.

SUGGESTIONS

In the research that has been done, there are still some limitations. Based on the results of the conclusions, as for suggestions that can be given, include: 1. For further researchers, because the results of research on Liquidity, Leverage, and Free Cash Flow show that companies do not experience the effect of financial distress on the samples that have been conducted, it is advisable to retest because it is not in accordance with the prevailing theory. Further researchers can also increase the number of research samples or compare manufacturing companies with other companies sub-sectors such as the food and beverage sub-sector, or even compare one sector with several companies between countries. 2. For the Company, it is expected to pay attention to factors that can cause the company's financial distress, so that if there is an indication the company is experiencing financial distress, the company can quickly take action to improve the company's financial condition.

REFERENCES

Ananto, Mustika, & Handayani. (2017). Pengaruh Good Corporate Governance (GCG), Leverage, Profitabilitas dan Ukuran Perusahaan Terhadap Financial Distress Pada Perusahaan Barang Konsumsi Yang Terdaftar Di Bursa Efek Indonesia. Jurnal Ekonomi & Bisnis Dharma Andalas, 19(1), 19–39. Asfali, I. (2019). Pengaruh Profitabilitas, Likuiditas, Leverage, Aktivitas, Pertumbuhann Penjualan Terhadap Financial Distress Perusahaan Kimia Imam Asfali. Jurnal Ekonomi Dan Manajemen, 20(2), 56–66. Bernardin, D. E. Y., & Tifani, T. (2019). Financial Distress Predicted By Cash Flow and Leverage With Capital Intensity As Moderating. Jurnal Apresiasi Ekonomi, 7(1), 18–29. https://doi.org/10.31846/jae.v7i1.188 Cinantya, I., & Merkusiwati, N. (2015). Pengaruh Corporate Governance, Financial Indicators, Dan Ukuran Perusahaan Pada Financial Distress. E-Jurnal Akuntansi, 10(3), 897–915. Curry, K., & Banjarnahor, E. (2018). Financial Distress Pada Perusahaan Sektor Properti Go Public di Indonesia. Seminar Nasional Pakar 1, (Buku 2), 207–221. Gobenvy, O. (2014). Pengaruh Profitabilitas, Financial Leverage dan Ukuran Perusahaan Terhadap Financial Distress Pada Perusahaan Manufaktur Yang Terdaftar di Bursa Efek Indonesia Tahun 2009 - 2011. Kasmir. (2012). Analisis Laporan Keuangan. RajaGrafindo. Li, J., & Du, W. (2011). An empirical study on the corporate financial distress prediction based on logistic model: Evidence from China’s manufacturing Industry. International Journal of Digital Content Technology and Its Applications, 5(6), 368–379. https://doi.org/10.4156/jdcta.vol5.issue6.44 Nisa, N., & Triyanto, D. N. (2018). Pengaruh Free Cash Flow, Financial Distress, dan Employee Diff Terhadap Manajemen Laba. Jurnal Akuntansi, Audit, Dan Sistem Informasi Akuntansi, 2(3), 93–104. Pernamasari, R., Purwaningsih, S., Tanjung, J., & Rahayu, D. P. (2019). Good Corporate Governance and Prediction of Financial Distress to Stock Prices : Atman Z Score Approach. 6(11), 56–62. Platt, H. D., & Platt, M. B. (2002). Predicting corporate financial distress: Reflections on choice-based sample bias. Journal of Economics and Finance, 26(2), 184–199. https://doi.org/10.1007/bf02755985 Rahmawati, M. (2014). Analisis Pengaruh Karakteristik Komite Audit Terhadap Financial Distress. 3, 1–8.

International Journal of Business, Economics and Law, Vol. 22, Issue 1 (AUGUST) ISSN 2289-1552 2020

Rohmadini, A., Saifi, M., & Darmawan, A. (2018). Pengaruh Profitabilitas, Likuiditas Dan Leverage Terhadap Financial Distress (Studi Pada Perusahaan Food & Beverage Yang Terdaftar Di Bursa Efek Indonesia Periode 2013-2016). Jurnal Administrasi Bisnis (JAB), 61(2), 11–19. Sayari, N., & Mugan, C. S. (2017). Industry specific financial distress modeling. BRQ Business Research Quarterly, 20(1), 45– 62. https://doi.org/10.1016/j.brq.2016.03.003 Sporta, F. O., Ngugi, P. K., Ngumi, P., & Nanjala, C. S. (2017). The Effect of Financial Leverageas a Financial Distress Factor on Financial Performance on Commercial Banks in Kenya. IOSR Journal of Business and Management, 19(07), 57–71. https://doi.org/10.9790/487x-1907035771 Srikalimah. (2017). JURNAL AKUNTANSI & EKONOMI FE. UN PGRI Kediri Vol. 2 No. 1, Maret 2017. 2(1), 43–66. Susilawati, D., Sofianty, D., & Sukarmanto, E. (2017). Pengaruh Profitabilitas , Ukuran Perusahaan dan Leverage Terhadap Financial Distress Pada Perusahaan yang Terdaftar di Bursa Efek Indonesia ( BEI ). Prosding Akuntansi, 3(2), 208–214. Triwahyuningtias, M., & Muharam, H. (2012). Analisis Pengaruh Struktur Kepemilikan, Ukuran Dewan, Komisaris Independen, Likuiditas Dan Leverage Terhadap Terjadinya Kondisi Financial Distress (Studi Pada Perusahaan Manufaktur Yang Terdaftar Di Bursa Efek Indonesia Tahun 2008-2010). Diponegoro Journal Of Management, 1(1), 1–14. Retrieved from file:///C:/Users/JAVIER/Downloads/30725.pdf Tutliha, Y. S., & Rahayu, M. (2019). Pengaruh Intangible Asset , Arus Kas Operasi Dan Leverage Terhadap Financial Distress. 2(1), 95–103. Wahono, Mardani, & Suproho. (2017). Pengaruh Likuiditas Leverage Dan Profitabilitas Terhadap Financial Distress Pada Perusahaan Transportasi Yang Terdaftar Di Bursa Efek Indonesia (Bei) Tahun 2011-2015. E-Jurnal Riset Manajemen, 179– 190. Retrieved from www.fe.unisma.ac.id Widhiari, N., & Aryani Merkusiwati, N. (2015). Pengaruh Rasio Likuiditas, Leverage, Operating Capacity, Dan Sales Growth Terhadap Financial Distress. E-Jurnal Akuntansi, 11(2), 456–469.

Angela Dirman Fakultas Ekonomi dan Bisnis Universitas Mercu Buana, 11610, Jakarta, Indonesia Email: [email protected]